Characterization of the Regulatory Network under Waterlogging Stress in Soybean Roots via Transcriptome Analysis

Yo Han Yoo, Seung Yeon Cho, Inhye Lee, Namgeol Kim, Seuk Ki Lee, Kwang Soo Cho, Eun Young Kim, Ki Hong Jung, Woo Jong Hong

Research output: Contribution to journalArticlepeer-review

Abstract

Flooding stress caused by climate change is a serious threat to crop productivity. To enhance our understanding of flooding stress in soybean, we analyzed the transcriptome of the roots of soybean plants after waterlogging treatment for 10 days at the V2 growth stage. Through RNA sequencing analysis, 870 upregulated and 1129 downregulated differentially expressed genes (DEGs) were identified and characterized using Gene Ontology (GO) and MapMan software (version 3.6.0RC1). In the functional classification analysis, “alcohol biosynthetic process” was the most significantly enriched GO term in downregulated DEGs, and phytohormone-related genes such as ABA, cytokinin, and gibberellin were upregulated. Among the transcription factors (TFs) in DEGs, AP2/ERFs were the most abundant. Furthermore, our DEGs encompassed eight soybean orthologs from Arabidopsis and rice, such as 1-aminocyclopropane-1-carboxylate oxidase. Along with a co-functional network consisting of the TF and orthologs, the expression changes of those genes were tested in a waterlogging-resistant cultivar, PI567343. These findings contribute to the identification of candidate genes for waterlogging tolerance in soybean, which can enhance our understanding of waterlogging tolerance.

Original languageEnglish
Article number2538
JournalPlants
Volume13
Issue number18
DOIs
Publication statusPublished - Sept 2024

Bibliographical note

Publisher Copyright:
© 2024 by the authors.

Keywords

  • RNA-seq
  • soybean
  • transcription factor
  • transcriptome analysis
  • waterlogging stress

Fingerprint

Dive into the research topics of 'Characterization of the Regulatory Network under Waterlogging Stress in Soybean Roots via Transcriptome Analysis'. Together they form a unique fingerprint.

Cite this